7 citations · 11 across the 5 of their papers we have counts for
5 papers
Generalized Category Discovery in Semantic Segmentation
Zhengyuan Peng, Qijian Tian, Jianqing Xu +5
This paper explores a novel setting called Generalized Category Discovery in Semantic Segmentation (GCDSS), aiming to segment unlabeled images given prior knowledge from a labeled…
AdaTriplet-RA: Domain Matching via Adaptive Triplet and Reinforced Attention for Unsupervised Domain Adaptation
Xinyao Shu, Shiyang Yan, Zhenyu Lu +2
Unsupervised domain adaption (UDA) is a transfer learning task where the data and annotations of the source domain are available but only have access to the unlabeled target data d…
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
Tianfang Sun, Zhizhong Zhang, Xin Tan +3
Weakly supervised point cloud semantic segmentation methods that require 1\% or fewer labels, hoping to realize almost the same performance as fully supervised approaches, which re…
Prototype-Aware Heterogeneous Task for Point Cloud Completion
Junshu Tang, Jiachen Xu, Jingyu Gong +3
Point cloud completion, which aims at recovering original shape information from partial point clouds, has attracted attention on 3D vision community. Existing methods usually succ…
LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypoints
Junshu Tang, Zhijun Gong, Ran Yi +2
Point cloud completion aims at completing geometric and topological shapes from a partial observation. However, some topology of the original shape is missing, existing methods dir…